The off-the-shelf package
Fast to install, but rigid. Your processes must bend to fit the tool. Whatever's missing is paid for in add-ons, Excel workarounds, or simply never gets done.
Our method
From need to production. No compromise on quality.
We industrialise business software: proven modules, tooled standards, and AI as both accelerator and quality guardrail. You keep control; we keep the rigour.
The real trade-off
Two ways to get it wrong
Before choosing a vendor, a company chooses a path. Most see only two — and both are costly, in their own way.
Classic custom development
Tailored to you, but fragile. Hand-built with no foundation or tests, it soon becomes impossible to maintain and breaks as it grows.
We hold the middle ground no one occupies: the engineering rigour of a large firm, at the cost and agility of a studio.
Why it's possible
An engine, not billable hours
Custom software is expensive when you start from scratch. We don't: we assemble and adapt a proven foundation. That's what makes a bespoke solution both affordable and robust.
A methodological framework
Technical expertise, engineering culture and AI leverage, combined into a repeatable way of working.
An in-house framework
IDS Platform: our proven, tested and evolving foundation that both speeds up and hardens every build.
Reusable business modules
Field service, after-sales, sales management, flex-office… already built, ready to adapt to your reality.
Integrated standard tooling
Monitoring, CI/CD, backup/restore, traceability, reporting: shipped by default, not as options.
AI, in its right place
AI accelerates. Humans decide.
We use AI where it is reliable — and nowhere it isn't. Two roles, in this order.
Accelerator and quality guardian
Internally, AI carries the repetitive work and continuous verification: automated functional and technical tests (load, scalability), code audit, standards compliance, architecture support. Robustness isn't added at the end — it's built at every step.
Embedded in your solution
When your business calls for it, we embed AI in the delivered product — search, automation, decision support — at a controlled cost, without the premium-suite surcharge.
AI does the repetitive work and verifies relentlessly. Our engineers decide the architecture, the scope and what ships to production. Judgment stays human; so does accountability.
The guardrails
We don't ask AI to be reliable. We make it impossible for it to drift.
Delegating execution only makes sense if drift is mechanically blocked. Four checks run on every integration — none optional, none depending on someone staying sharp on a Friday evening.
- 01
A broken architecture rule breaks the build
The business core may not depend on infrastructure. This is not a convention a review might wave through: it is a test that fails and stops the pipeline.
- 02
A broken event contract is caught in continuous integration
The schema of every event exchanged between services is generated from the code and verified automatically. An incompatible change cannot slip through unnoticed.
- 03
The tests are themselves tested
We deliberately inject defects into the code: if the tests stay green, they were testing nothing. High coverage proves little; this proves a lot.
- 04
APIs are verified end to end
Every endpoint is exercised automatically against a real database, and code quality must clear a blocking threshold before any merge.
Judgement stays human. Discipline, on the other hand, is executable.
The maturity scale
When a module becomes a product
"Our products are not demos" is an easy thing to say. Here is the rule that makes it verifiable — written down, dated, and open to challenge.
- 01
Proven in the field
The module was born of a real client need and runs in their production. Nothing more, at this stage.
- 02
Industrialised
Two distinct client projects use it — and neither required diverging from the core. Their specifics went through extension points and configuration.
- 03
Product
Three projects, configuration without writing code, and six months of stable releases. Then, and only then, we call it a product.
After go-live
Delivery is not the end. It is where operations begin.
The question everyone asks last — "and then, who maintains it?" — should be asked first. Here is our answer.
Monitoring and alerting
The application is instrumented from day one: metrics, logs, traces. An incident is seen before the user picks up the phone.
Backups with proven restore
Daily backups and continuous archiving, allowing a return to any point in time. A backup that has never been restored is not a backup.
A disaster-recovery plan actually tested
Not a document: a full cloud migration, executed for real. We know how long it takes to come back up, because we have done it.
A partner over the long run
The industrial ERP we are rebuilding has been running for fourteen years, and the relationship with that client — begun by our CTO, carried on by INNOV DS — is sixteen years old. Maintenance is not an option you discover at renewal time.
The outcome
Robust, simple, yours
Robust by construction
Tests, standards and mastered architecture: quality is proven, not promised.
A UX that's finally simple
Software that fits your business is picked up without endless training.
Your code, your data
You own the solution. Source code and data delivered: full reversibility, zero lock-in.
Controlled cost and timeline
Reuse and tooling make custom software predictable — at the price of a standard package.
What about security?
Centralised authentication and single sign-on, fine-grained authorisation — by role, by attribute, by relationship —, strict separation between public channels and the back office. Security is not a layer added at the end: it is in the architecture.
The proof
The method, already in production
Our products aren't demos. They're modules born from real client missions, capitalised on IDS Platform — living proof of the engine.
Nexflow
Field service
FlowSpace
Flex-office
SAV
After-sales & warranties
gescom
Sales management & export customs
NexHub
Cross-cutting modules
Step by step
From need to production, in five moves
Here's concretely how we move forward — and where the guardrails are.
- 01
Understand
- What we do
- Frame the real need, analyse the existing landscape (processes, data, regulatory constraints).
- Where AI helps
- Research and synthesis, mapping of code and dependencies.
- What you see
- A clear scope and shared priorities.
- 02
Design
- What we do
- Define the architecture, break work into deliverable increments, document decisions.
- Where AI helps
- Option exploration, impact and dependency checks.
- What you see
- A plan approved before a single line of code.
- 03
Build
- What we do
- Develop in short increments, reuse our modules, apply the standards.
- Where AI helps
- Tooled generation under constraints, continuous code review.
- What you see
- Visible progress, no tunnel effect.
- 04
Qualify
- What we do
- Test (functional and technical), review, cross a checkpoint only with green tests.
- Where AI helps
- Automated test suites, regression detection.
- What you see
- Quality proven at every step, not at the end.
- 05
Deliver & operate
- What we do
- Tooled production release, monitoring, backups, ownership handover.
- Where AI helps
- Monitoring, alert correlation, diagnostics.
- What you see
- A stable solution — and control over your asset.
At every checkpoint, a human decides. And when reality upsets the plan, the method adapts — without ever skipping validation.
Contact
Let's talk about your project.
Tell us about your process: we'll tell you honestly what's feasible, at what cost and in what timeframe.